modeling and load flow analysis of a microgrid laboratory
TRANSCRIPT
IJSGSET TRANSACTIONS ON SMART GRID AND SUSTAINABLE ENERGY, VOL. 3, NO. 2, NOVEMBER 2019 103
Modeling and Load Flow Analysis of a Microgrid
Laboratory
Taufik*, Matthew A. Guevara, Ali Shaban and Ahmad Nafisi
Abstract—Microgridsminiature versions of the electrical
grid are becoming increasingly more popular as advancements
in technologies, renewable energy mandates, and decreased
costs drive communities to adopt them. The modern microgrid
has capabilities of generating, distributing, and regulating the
flow of electricity, capable of operating in both grid-connected
and islanded (disconnected) conditions. This paper utilizes
ETAP software in the analysis, simulation, and development of
a lab-scale microgrid located at Cal Poly State University.
Microprocessor-based relays are heavily utilized in both the
ETAP model and hardware implementation of the system.
Three case studies were studied and simulated to investigate
electric power system load flow analysis of the Cal Poly
microgrid. Results were compared against hardware test
measurements and showed overall agreement. Slight
discrepancies were observed in the simulation results due
mainly to the non-ideality of actual hardware components and
lab equipment.
Index Terms: microgrid, power engineering laboratory,
ETAP modeling, power system education.
I. INTRODUCTION
icrogrids as the scaled down versions of our
electrical grid are becoming increasingly more
popular as greater energy independence and
extreme weather conditions drive communities to adopt
them. Conventionally, electrical power is delivered by
utilities from large power generating stations far away from
end users, transmitted across long distances, and ultimately
distributed to meet the customers’ electrical needs.
Advancements in technologies, decreased costs, and
renewable energy mandates are shifting the power industry
away from this centralized generation model. Instead,
utilities are observing their customers not only as energy
consumers but also actively producing electrical power. The
modern microgrid has capabilities of generating,
distributing, and regulating electrical power locally, utilizing
distributed energy resources (DERs) situated close to end
users, including smaller power sources such as photovoltaics
(solar) and battery energy storage systems to meet the
electrical demands of the customer.
Manuscript received July 11, 2019; revised September 10, 2019;
accepted October 15, 2019.
Taufik is with Electrical Engineering Department, Cal Poly State University, San Luis Obispo, USA (e-mail: [email protected]).
Matthew A. Guevara, Ali Shaban and Ahmad Nafisi Electrical
Engineering Department, Cal Poly State University, San Luis Obispo, USA (e-mail: maguevar, ashaban, [email protected]).
*Corresponding author.
The microgrid has capabilities of operating in both grid-
connected and islanded modes—that is, connected or
disconnected from the larger electrical grid, respectively.
From the customer perspective, this presents several
advantages—for example, if a power outage were to occur
on the main grid due to natural disasters or electrical faults,
the microgrid can island from the grid and continue its
generation and distribution of local power. Additionally, if
the microgrid requires additional generation to meet the
demands of the customer, the microgrid can reconnect with
the main grid to help supplement the customers’ energy
needs.
From the utility perspective, transitioning the microgrid
from grid-connected to islanded conditions presents both
advantages and disadvantages. A 2014 survey of over 250
utility executives concluded “…utilities said they find
current interconnection standards inadequate for safety
purposes, with 54% of utilities surveyed finding that to be
the case” [1]. As microgrids continue to rise in popularity, it
is imperative to study and implement reliable and robust
protection schemes as microgrids transition between grid-
connected and islanded conditions. Nonetheless, reference
[2] claims “microgrids deployment of controllable
resources, such as dispatchable generation units, energy
storage, and adjustable loads, provides a quick and efficient
response for changing the microgrid generation/load, which
can be utilized for supporting the grid operation.”
Maintaining the balance between power supply and load has
become problematic for utilities in recent years. Microgrids
can be implemented to help control and supplement the
supply-load balance by offering storage and generation
services to the main grid.
Figure 1 shows a net load graph by California ISO
(CAISO), displaying the net load in 2013 and forecasted
future net loads [3]. The net load curves indicating years
2014-2020 can be interpreted as the net power needed to be
supplied to California’s customers from all sources of
electrical power other than from renewables. The lowest
points on the curve (the belly of the “duck”) represents a
point in which renewable generation is at a maximum. Data
indicates that risks of over generation and necessary ramping
power is increasing in future years largely due to growing
solar photovoltaic proliferation onto the grid. Currently, grid
operators need to closely monitor these curves and curtail or
dispatch electrical power as needed. Microgrids can be
utilized to help “flatten” this duck curve to maintain the
supply-load balance and retain grid reliability in several
ways. For example, when renewable penetration is at a
maximum leading to risks of over generation, the microgrid
can store excess energy with a battery energy storage system.
As the sun begins to set after 4pm and aggregate solar
penetration to the main grid begins to decrease, microgrids
M
104 IJSGSET TRANSACTIONS ON SMART GRID AND SUSTAINABLE ENERGY, VOL. 3, NO. 2, NOVEMBER 2019
can help supply the necessary ramping power needed to meet
the electrical demand of California’s customers.
Fig. 1. The CAISO duck chart for 2013.
Figure 2 showcases the opportunities ahead for utilities,
based on a survey of over 250 utility executives in 2014 [1].
A staggering 97% of utility executives believe microgrids
are a viable business opportunity within the next 10 years,
with a majority of utilities already developing or planning to
operate microgrids within the same timeframe.
Fig. 2. The opportunities ahead: Utilities
Microgrids are an inevitable reality—critical loads such
as hospitals, data centers, and military bases can benefit
greatly from increased reliability of electric power in both
grid-connected and islanded conditions. Microgrids can also
support grid operation by storing and dispatching electrical
energy as necessary. It is then imperative for future power
system engineers to expand their knowledge on fundamental
power system components such as generators, transformers,
and protective relaying to account for emerging technologies
onto the grid.
II. MICROGRID MODELING AND STABILITY ANALYSIS
Future trends of developing microgrids and their
integration with the utility grid necessitate adequate tools for
modeling and analysis purposes. In response for “facing a
rapidly-changing power industry, the electrical engineering
department at Cal Poly State University proposed Advanced
Power Systems Initiatives to better prepare its students for
entering the power industry” [4]. One effort to accomplish
as presented in this paper is the development of the
foundation for a lab-scale microgrid laboratory. To
ultimately implement a microgrid capable of islanding
capabilities, it is imperative to first develop an adequate
model of the microgrid and perform a system stability
analysis.
Figure 3 displays the single-line diagram of the
bidirectional network designed and implemented in a
laboratory environment for the proposed lab [4], which is to
be utilized as the basis for the microgrid. The network
represents two different radial power systems coupled
together at bus 3. In this configuration multiple sources of
power supply the loads at bus 3, which include the induction
motor and static loads. The power is supplied by three-phase
AC voltages, modeled as infinite buses in Figure 3,
ultimately supplied by the utility. Common power system
components including power transformers and transmission
lines are implemented, as well as resistors to limit the total
current flowing in the systems.
Fig. 3. Bidirectional network single-line diagram
Fig. 4. Bidirectional network single-line protection diagram.
Figure 4 displays the existing protective elements within
the bidirectional network [4], completed in May 2017.
Microprocessor based SEL (Schweitzer Engineering
Laboratories) protective relays are constantly measuring
power system parameters such as voltages and currents,
ultimately sending trip signals to nearby circuit breakers to
protect nearby components in the event of a disturbance such
as a fault. The SEL relays are programmed to trip circuit
breakers on parameters such as the type of fault, equipment
and zone of protection, and protection coordination between
relays.
The future microgrid will additionally include other
DERs such as photovoltaics and battery storage systems. As
the microgrid expands in complexity with added equipment
and functionality, it is necessary to develop an adequate
model of the system. ETAP is a power system modeling,
analysis, and optimization software. ETAP enables its users
with several tools to accurately model power systems that
will ultimately benefit the microgrid project moving
forwards. For example, ETAP network analysis tools
include standard load flow, short circuit, motor acceleration,
and harmonic analysis. Protection and coordination tools
include ETAP “STAR” modules to coordinate time-current
curves associated with microgrid protective elements.
As the microgrid begins to implement its DERs beginning
with additional synchronous generators as shown in Figure
4, synchronous generator protection and coordination can be
adequately modeled in ETAP. Future additional DERs
TAUFIK, et al.: MODELING AND LOAD FLOW ANALYSIS OF A MICROGRID LABORATORY 105
appended to Cal Poly’s microgrid including photovoltaics
and battery storage systems can be sufficiently modeled and
analyzed in ETAP. A system analysis will then be performed
including load flows, short circuits, and protection
coordination studies.
The bidirectional network in Fig. 4 for use as the basis for
the microgrid assumed two states—steady or faulted. Power
systems are largely imbalanced in nature and consistently
undergoing small scale disturbances. Reference [5] defines
power system stability as “…the ability of an electric power
system, for a given initial operating condition, to regain a
state of operating equilibrium after being subjected to a
physical disturbance, with most system variables bounded so
that practically the entire system remains intact.” Power
system stability can then be observed as a single problem
with many different classifications of instability that can
result from various disturbances, with their forms
generalized in Fig. 5 [5].
Fig. 5. Classification of power system stability
Stability in a microgrid shares similarities with classical
power system stability classifications shown in Fig. 5, with
additional issues such as disturbances resulting from
islanding. Reference [6] suggests “with micro sources with
current limit, very little spinning reserve and limited reactive
support, it is essential to carry out detailed transient analysis
with possible contingencies,” with Fig. 5 showcasing
microgrid stability issues. Unlike microgrids with limited
resources, the bulk power system typically has excess
generating capacity, or operating reserves, to meet real and
reactive demands to maintain stability [7][8].
Fig. 6. Different stability issues in microgrid
III. DESIGN REQUIREMENTS
Figure 7 shows a level zero block diagram used for
developing the ETAP model of the Cal Poly microgrid.
Fig. 7. ETAP model level 0 block diagram.
Inputs to the ETAP model block diagram include the
entirety of the existing microgrid components including
synchronous generators, induction motor, static loads, power
transformers, utility grid, protective elements, busbars, and
cables. Input devices that are currently not implemented in
the existing microgrid include solar photovoltaics and
battery storage systems. However, these modules will
ultimately be modeled in ETAP to explore and analyze the
functionality of the microgrid as the project develops.
Outputs to the ETAP model block diagram in Fig. 7
include load flow, short circuit analysis, and protection
coordination. ETAP Load Flow Analysis module will be
utilized to determine bus voltages, power factors, currents,
and power flows throughout the microgrid system. To
determine bus voltages, angles, and power flows, ETAP
Load Flow allows several different load flow calculation
methods. To perform the load flow study, each calculation
method contains different load flow converging
characteristics, allowing flexibility to meet the microgrid
system parameters including generation, loading conditions,
and initial bus voltages [9].
The ETAP Short Circuit analysis program will be utilized
to analyze the fault currents for three-phase, line-to-ground,
line-to-line, and line-to-line-ground faults in the microgrid.
ETAP is able to calculate the total short circuit current
contribution from microgrid elements including the
synchronous generators, induction motor, and utility
connections. ETAP includes both American National
Standards Institute/Institute of Electrical and Electronics
Engineers (ANSI/IEEE) and International Electrotechnical
Commission (IEC) standards to perform its short circuit
calculation methods [10].
The microgrid will utilize ETAP Star, the protection and
coordination (selectivity) module within ETAP. ETAP Star
is equipped with a comprehensive protective device library,
able to accurately model protective elements to perform
equipment protection and device coordination studies [10].
ETAP Star Time Current Characteristic (TCC) views will be
generated to display device characteristic curves. ETAP Star
is also capable of determining operating times of protective
devices by simulating faults on the one-line diagram.
ETAP
MODEL
Synchrounous Generator
Induction Motor
Static Load
Power Transformer
Utility Grid
Protective Elements
Busbars
Cables
Solar Photovoltaic
Battery Storage
Load Flow
Short Circuit Analysis
Protection Coordination
106 IJSGSET TRANSACTIONS ON SMART GRID AND SUSTAINABLE ENERGY, VOL. 3, NO. 2, NOVEMBER 2019
IV. DESIGN
The ETAP Cal Poly microgrid elements in Fig. 8 include
the power grid, impedances, circuit breakers, power
transformers, three-phase induction motor, static loads,
circuit breakers, current transformers (CTs), potential
transformers (PTs/VTs), and protective relays. Power
system elements not shown in Fig. 8 include future additions
such as solar photovoltaics, inverters, and energy storage
modules.
Fig. 8. ETAP one-line view.
The Power Grid element in ETAP models the utility
interconnection with the microgrid. The proposed microgrid
lab at Cal Poly utilizes 208V, modeled as the utility supply
voltage. As such, the Power Grid is rated for 208V operating
in swing mode. The Power Grid in ETAP is modeled with its
Thevenin’s equivalent, a constant voltage source behind a
short-circuit impedance. The Short Circuit page in the Power
Grid editor provides information necessary to model the
utility grid as a source for studies including Short Circuit and
Transient Stability. Relevant data include line voltage, short-
circuit MVA, three phase fault currents, and X/R ratios.
The Impedance elements in ETAP are utilized to model
10Ω resistors and 45mH inductors existing in the Cal Poly
microgrid. The resistors in the microgrid are utilized for
current-limiting purposes for safely testing power system
faults. The inductors are utilized to model transmission lines
of a power system. Although there exists a detailed
Transmission Line and Reactor elements in ETAP, it is
unnecessary in the modeling of inductors utilized in the
microgrid.
The Power Transformer element in ETAP models two-
winding three single-phase transformers in the Cal Poly
microgrid with a 1:1 turns ratio rated at 3KVA, 240V, and z
= 2.5%. The transformers were included to more accurately
model a complete power system and utilized for protective
relaying test. Two power transformers are modeled
connected in wye-wye configurations.
The Induction Machine element in ETAP models the
three-phase induction motor. The ETAP element models the
Hampden IM-100, a one-third horsepower three-phase, four
pole, and squirrel cage motor with a wound stator and a
squirrel cage rotor, utilized for loading purposes. Induction
motor power and impedance parameters will play a role into
short circuit and stability simulations. Due to resistive losses
in the system, voltages applied at the terminals of the
induction motor will be less than 208Vac in a laboratory
setting. Induction motor parameters will be largely based on
laboratory tested ratings rather than nameplate ratings.
The Static Load element in ETAP models two Hampden
RLC-100 resistive/reactance loads utilized in the microgrid.
The loads are connected in parallel, providing resistive
loading controlled by 6 toggle switches (12 total), each one
inserting a 2000Ω resistor in parallel in each leg
simultaneously (to a minimum of 167Ω). That is, at
maximum loading the two three-phase static loads consume
a total of
WV
P LL 259333
)120(32 2
max
(1)
at a nominal 208Vac line-to-line. Due to resistive losses in
the system, voltages applied to the static loads will be less
than 208Vac in a laboratory setting. Static load parameters
will be largely based on laboratory tested ratings rather than
nominal values.
The Synchronous Generator element in ETAP models two
Hampden SM-100-3, three-phase, four pole machines
consisting of a wye/delta stator and quadrature rotor having
a DC field winding and a damper winding. DC field
excitation is controlled by an external variable resistor
(rheostat) supplied by 125V DC. The rotor of the
synchronous generator is driven by a DC machine, Hampden
DM-100 providing one-third horsepower at 1800 rpm. SEL
microprocessor based relays will be utilized to obtain
oscillograms of the generator current and voltage
characteristics, in which short circuit characteristics can be
extracted.
The Relay elements in ETAP models Schweitzer
Engineering Laboratory (SEL) microprocessor based
protective relays include SEL-387E, SEL-311L, SEL-710,
SEL-587, SEL-700G, and SEL-421 [4]. Current
transformers (CTs) and potential transformers (VTs/PTs)
shown in the ETAP model are utilized to feed SEL relays
electrical quantities to determine the status of the microgrid.
Due to low nominal and fault currents, the CTs and PTs are
included in the one-line diagram to adhere with ETAP
modeling standards, and do not exist in the hardware
implementation. Therefore, the CTs and PTs throughout the
ETAP model have a 1:1 turns ratio.
Figure 9 showcases a subsystem of the ETAP model
where small scale solar photovoltaic generation complete
with an inverter to interconnect with the microgrid is a
logical addition to the system. ETAP consists of in depth
solar photovoltaic and inverter modeling tools to accurately
represent Cal Poly’s renewable integration with the
microgrid. ETAP is equipped with maximum power point
tracking control capabilities with its solar inverters to adjust
operating points for solar panels to extract maximum power.
The SEL-751 in Fig. 9 can provide additional protective
capabilities to the system [12].
Fig. 9. ETAP microgrid sub-system.
TAUFIK, et al.: MODELING AND LOAD FLOW ANALYSIS OF A MICROGRID LABORATORY 107
As an example, a PV module tentatively chosen for the
Cal Poly microgrid modeling purposes is the SUNTECH
STP210. Figure 10 displays the PV Array editor when
double left clicking the PVA1 module in Fig. 9. Under the
PV Panel page, the P-V curves display the power-voltage
characteristics of a solar module for various levels of solar
irradiance, a measure of energy in the form of sunlight.
Similarly, the nonlinear I-V curves describe the current-
voltage characteristics of the solar cells for various levels of
irradiance. ETAP has extensive libraries for various power
system components, and the curves and parameters shown in
Fig. 10 are populated when selecting the STP210 module
from the library. Alternatively, a user can generate these
curves individually by creating an ETAP PV Array library
file given known equivalent circuit parameters of a solar cell,
providing users with tools to accurately model a PV system.
The ETAP Inverter will be utilized to convert the DC
characteristics from the PV array into the three-phase AC
system, modeling the grid-tie inverter. The Inverter Editor
can control and modify several parameters including
converter’s efficiency, generation for AC Load Flow
calculations, and harmonics of the device. Power quality
considerations can be analyzed by harmonics analysis tools
in ETAP, and Fig. 11 displays the Harmonic tab of the grid-
tied inverter. The harmonics of a specific device can be
chosen from a list of libraries in ETAP or entered given
device characteristics.
Fig. 10. PV array editor.
Fig. 11. Inverter editor.
Additionally, energy storage systems can be appended as
additional generation and loading systems. Additional SEL
relays can be utilized with solar integration to provide a more
dynamic element to the system. That is, SEL relays can
continually sense electrical quantities including voltages,
currents, and frequencies from a PV subsystem to determine
if curtailment or generation of renewable energy is necessary
[13]. This can further lead to stability improvement methods,
with control of power electronics providing many
advantages to the microgrid.
For the load flow analysis, the purpose is to determine the
balanced three-phase steady state operation of the Cal Poly
microgrid. The load flow study will be performed in ETAP
to meet the microgrid requirements of generation adequately
supplying the demand (load) and losses, bus voltages close
to nominal values, generation operating within active and
reactive power limits, and transmission line (inductor) and
transformers not overloaded [11]. Equipment operating
values against manufacturer’s specified maximum capability
ratings will be compared when available.
The load flow study will consider several different
operation scenarios such as maximum loading, minimum
loading, normal loading, grid-connected, and islanded
conditions. The Loading tab of the Load Flow Study Case
editor shows Generation Category operating under Design.
This forces the Load Flow study to consider all generating
units in ETAP to operate under their Design operating
conditions. For example, if we double left click a
synchronous generator in the ETAP one-line, we open the
Synchronous Generator Editor whose Design category is set
to operate at 0.2 kW and 0.05 kvar, illustrated in Fig. 13. The
Synchronous Generator is set to operate under Mvar Control
instead of Swing Control in the Info page (not shown), to set
fixed active and reactive power output of the machines. This
will be useful as we can perform accurate case studies for
generators outputting specific active and reactive power.
Additionally, this is also due to the inherent limitations of
the microgrid in which we do not implement generator
exciter and governor control.
Fig. 12. Synchronous generator editor.
The main purpose of a short circuit study in the context of
the Cal Poly microgrid lab is to ultimately determine
appropriate ratings and settings for protective relay
coordination by analyzing the effect of different faults
injected in the system. Short circuit studies enable
108 IJSGSET TRANSACTIONS ON SMART GRID AND SUSTAINABLE ENERGY, VOL. 3, NO. 2, NOVEMBER 2019
verification of protective device interrupting capabilities
(e.g. circuit breakers), as well as protect equipment from
large electromagnetic and mechanical forces due to high
fault currents. However, fault currents in the Cal Poly
microgrid are deliberately minimized due to safety
considerations, and as a result of utilizing smaller rated
equipment (e.g. 1/3rd horsepower motors and generators).
ETAP elements that contribute to a short-circuit fault current
include synchronous machines, induction machines, and the
power (utility) grid. Additional modifications to the
microgrid including inverters and batteries will also
contribute to short-circuit currents.
V. SIMULATION AND TEST VALIDATION
Figures 13 and 14 display the hardware and ETAP
implementation of the microgrid system, separated between
two different sections.
A. Case 1: Bidirectional System, No Motor & Capacitor
Table I displays laboratory measured data of the
microgrid to gather load flows throughout the system
obtained from a previous study [14]. In this scenario the
excitation voltage and the output power of the generator is
manually adjusted by setting the speed of the prime mover
(DC motor). Each synchronous generator is operating at
100W, 12Var, supplying a total of 200W and 24Var.
Fig. 13. Utility to Bus 3 hardware lab setup (top) and ETAP model (bottom).
Figure 15 provides a load flow comparison of a one-line
depicting the apparent power (VA) and amps (A) flowing
throughout the system. All sources of generation are selected
to operate in swing mode. The utility supplies the power
flowing from Bus 2 to Bus 3, and the generators supply the
power flowing from Bus 4 to Bus 3. De-energized elements
are grayed out (motor and capacitor).
Fig. 14. Generator to Bus 3 hardware lab setup (top) and ETAP model
(bottom).
TABLE I. SYSTEM SYNCHRONIZED, NO MOTOR, NO CAPACITORS
Location
Real
Power
[W]
Current
[A]
Voltage
[V]
Reactive
Power
[VAR]
Apparent
Power
[VA]
Power
Factor
Generator
Utility
Motor
200
133.8
0
.563
.369
0
208
207.6
194
24
54.6
0
235
152.6
0
.857
.739
1
Fig. 15. Load flow for Case 1.
In Fig. 15, the total current supplied to the static loads at
Bus 3 is 0.696 A. However, laboratory tested data in Table I
suggests total current from utility and the generators supply
about 0.932 A. The discrepancies between the two data can
be attributed to transformer magnetizing current and
saturation, both of which are not modeled in ETAP.
TAUFIK, et al.: MODELING AND LOAD FLOW ANALYSIS OF A MICROGRID LABORATORY 109
Consider Fig. 16 in which the synchronous generators are
instead operated in Mvar mode, where the user can enter
specific values of active and reactive power generation from
the rating page of the synchronous generator models. The
utility is still selected as swing mode, supplying the
remaining power and balancing load flow in the system. We
can observe that the power flowing from Bus 4 to Bus 3 from
the generators closely matches that of Table 5-1 of 200 W
and 24 Var.
However, we have compromised the remaining power
flowing from the utility in this configuration. This is the
inherent limitation of ETAP load flow modeling of non-ideal
components largely due to the transformers drawing
additional current throughout the system. Therefore, even if
the generators are modified to supply specific fixed amounts
of reactive and active power, the ETAP model will not
accurately represent the hardware representation of the
system, and there will be less total power flowing in the
system when compared to laboratory data.
Fig. 16. Load flow for Case 1 in MVAR mode
B. Case 2: Bidirectional System with Motor & Capacitors
Table II showcases microgrid system data with the motor
and capacitor both turned on [14].
TABLE II. SYSTEM SYNCHRONIZED WITH MOTOR & CAPACITORS
Location
Real
Power
[W]
Current
[A]
Voltage
[V]
Reactive
Power
[VAR]
Apparent
Power
[VA]
Power
Factor
Generator
Utility
Motor
200
184.9
76.9
.6
.562
.268
208
206.4
187
130
58.5
40
250
232.5
87
.799
.797
.00
Figure 17 displays the load flow with all generations as
swing buses for purposes of simulation. Power flow between
Bus 4 and Bus 3 from the generators and between Bus 2 and
Bus 3 from the utility results in a smaller current than that
shown in Table II. This is again due to the inherent limitation
of limited reactive power flow in the system as mentioned in
Case 1 of load flow analysis. Next we apply a wye-connected
capacitor bank of 25 µF each energized at 185 V line-to-line
supplying a total of 323 Var at the motor bus, shown in Fig.
17. Bus voltages are increased by providing reactive power
support to the system. Additionally, the lowering of apparent
power and current is seen from Bus 2 to Bus 3 and Bus 4 to
Bus 3, which are the apparent power and current flow from
the utility and generators, respectively.
Fig. 17. Load flow for Case 2.
C. Case 3: DC Load Flow
Case 3 of Load Flow analysis considers some of the
capabilities and possibilities of running DC load flow
simulations. The future microgrid lab will utilize BP SX
150S Solar Panels rated at 150 W, open circuit voltage of
43.5 V, short circuit current of 4.75 A, maximum power
point operating voltage at 34.5 V, and maximum power point
current of 4.35 A. The inverter to connect to the AC system
will be the APsystems 1000W YC-1000 3-phase microverter
[15]. For purposes of simulations, the Photowatt PV1400
will be used as a model in ETAP for conduction DC Load
Flow, rated at 150 W, maximum power point operating
voltage at 33.69 V, and maximum power point current of
4.45 A, which closely model the BP SX 150S.
Solar panel ratings are provided based on standard test
conditions and several conditions such as solar irradiation,
module temperature, angle with respect to the sun and others
as presented in [16]. For purposes of simulations we utilize
standard test conditions of 25 degrees Celsius, and set an
irradiance of 200 W/m2 for four PV1400 panels, with a DC
load flow shown in Figure 18.
Fig. 18. DC load flow for Case 3.
110 IJSGSET TRANSACTIONS ON SMART GRID AND SUSTAINABLE ENERGY, VOL. 3, NO. 2, NOVEMBER 2019
The inverter can be operated as MVAR controlled AC
operation mode, similar to that of the synchronous
generators. With a 95% efficiency, we can specify the AC
output to be 95 W, or any specific fixed amount of the input
DC power from the solar panels. Cable impedance is
neglected for purposes of simulation, but can be entered if
losses are needed. This shows the capabilities of the DC load
flow: ability to investigate different PV generating
parameters and determine output AC power and supply
known power to the microgrid accordingly. Figure 19
displays an AC Load Flow taking into account the DC power
supplied by the panels. The generators are heavily relieved
from the active power demanded from the system,
supplemented from solar generation. The synchronous
generators instead provide mostly reactive support to the
system. The generators and utility are operating in swing
mode, while the inverter is operating in MVAR with fixed
output of 95 W. The motor is turned on, with the capacitor
off. The DC_system subsystem block in Fig. 19 contains the
DC system depicted in Fig. 18.
Fig. 19. AC load flow with PV generation.
VI. CONCLUSION
Advancements in renewable energy technologies along
with their decreasing costs and renewable energy mandates
are shifting the power industry away from the centralized
generation model and instead incorporate distributed energy
resources close to end users to meet the electrical demands
of the customer. The modern microgrid has capabilities of
operating in both islanded and grid-connected modes to help
supplement the transfer of energy. This paper describes the
development of an ETAP model of a lab-scale microgrid
currently developed at Cal Poly State University and test its
load flow performance. Several case studies and system
validations comparing the ETAP model with the Cal Poly
microgrid were conducted, showcasing the powerful
analysis tools ETAP can offer. Successful replication of both
short circuit and protection coordination studies were
validated for both the hardware and ETAP implementations
of the microgrid.
Cases I-III of Load Flow analysis considered different
variations of the bidirectional microgrid system. In all cases,
total power supplied from generation is lower than the
hardware implementation of the microgrid. This is due to
inherent limitations of the Load Flow analysis module which
does not consider the effects of transformer magnetizing
current and saturation. Case III also considered the DC Load
Flow in which PV panels were utilized to supplement active
power in the system. The future microgrid can vary the
amount of panels based on power demand, and utilize the
generator(s) for reactive power support.
Load flow and transient stability studies were the most
difficult studies to accurately model the Cal Poly microgrid
due to several considerations: non-ideal low rated
equipment, low time constants associated with dampening of
transients, and low system inertia. Magnetizing current and
transformer saturation could not be modeled in ETAP load
flow analysis, resulting in less current flowing throughout
the system and higher overall bus voltages. ETAP is
originally designed to model industrial scale and larger
power systems, whereas the rotating machineries in the Cal
Poly’s microgrid lab are rated at one-third horse power with
very low rotational inertia.
REFERENCES
[1] “The Utility View Of Microgrids,” Utility Dive. 2014. [2] A. Majzoobi and A. Khodaei, “Application of microgrids in providing
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[4] K. Pretzer, “Protective Relaying Student Laboratory,” Master’s
Thesis, Dept. Elect. Eng., California Polytechnic State Univ., San Luis Obispo, 2017.
[5] P. Kundur et al., "Definition and classification of power system
stability IEEE/CIGRE joint task force on stability terms and definitions," IEEE Transactions on Power Systems, vol. 19, no. 3, pp.
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[7] R. Singh and M. Kirar, "Transient stability analysis and improvement in microgrid," in 2016 International Conference on Electrical Power
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[9] J. McCalley. EE 554. Class Lecture, Topic: “Preliminary
Fundamentals.” College of Engineering, Iowa State University, Ames, Iowa, Spring 2009.
[10] ETAP 14.1 User Guide. Operation Technology, Inc.
[11] J. D. Glover, T.J. Overbye, and M.S. Sarma, Power system analysis and design, 5th ed. Stamford, CT: Cengage Learning, 2012. Print.
[12] A. Shaban, and A. Nafisi. EE 518. Class Lecture, Topic: “Symmetrical
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content/uploads/2017/07/APsystems-YC1000-Datasheet-7.20.17.pdf
[16] Yang, Woo-Sik “Microgrid Laboratory,” Senior Design Project, Dept. Elect. Eng., California Polytechnic State Univ., San Luis Obispo,
2018.
BIBLIOGRAPHY
Taufik received his BS in Electrical Engineering
with minor in Computer Science from Northern Arizona University, MS in Electrical Engineering
from University of Illinois Chicago, and Doctor of
Engineering from Cleveland State University. He is currently a Professor and the Director of Electric
Power Institute at Cal Poly State University in San
Luis Obispo. He is a Senior Member of IEEE and has industry experience with engineering companies
including Capstone Microturbine, Rockwell
TAUFIK, et al.: MODELING AND LOAD FLOW ANALYSIS OF A MICROGRID LABORATORY 111
Automation, Picker International, San Diego Gas & Electric, Diodes Inc., Enerpro, and Sempra Energy. He has published over 200 technical papers
and journals, reports, books, course readers, and served on the editorial
review boards of several journals. His areas of research include power electronics, power systems, energy harvesting and renewable energy.
Matthew Guevara received his BS in Electrical Engineering from California State University at
Northridge, and in 2018 graduated with MS in
Electrical Engineering from Cal Poly State University in San Luis Obispo. He is currently an
electrical engineer at Los Angeles Department of
Water and Power. His interest is in the broad area of power systems and power electronics.
Ali Shaban received his Ph.D. degree in Electrical
Engineering from Oregon State University in 1985. He joined the Electrical Engineering
Department at Cal Poly in 1984. Since 1985, he
has done consulting work with Chevron, Southern California Edison, JPL Scientific, and Bluepoint
Associates, Ltd., in San Luis Obispo. His field of
interest is electric machines, power quality, power systems analysis, and power systems protection.
He has published in the areas of synchronous
machines, induction motor, reliability, and power quality. He is a member of the IEEE and PES.
Ahmad Nafisi received his Ph.D. degree in Electrical Engineering from University of Southern
California in 1983. He joined the Electrical
Engineering Department at Cal Poly in 1984. He has done consulting and research activities with
Electro-Kinesis, Inc. (a Division of Superior
Electric Company), Southern California Edison, PG&E, and Los Angeles Department of Water and
Power. He was the director of Cal Poly Electric
Power Institute from 1998-2010. His field of interest are electric machines, power systems analysis, power quality, and
magnetic materials. He is a member of the IEEE and PES.